Vision is the principal source of information of the surrounding world. It facilitates our movement and development of everyday activities. In this sense, blind people have great difficulty for moving, especially in unknown environments, which reduces their autonomy and puts them at risk of suffering an accident. Electronic Travel Aids (ETAs) have emerged and provided outstanding navigation assistance for blind people. In this work, we present the methodology followed for implementing a stereo vision‐based system that assists blind people to wander unknown environments in a safe way, by sensing the world, segmenting the floor in 3D, fusing local 2D grids considering the camera tracking, creating a global occupancy 2D grid, reacting to close obstacles, and generating vibration patterns with an haptic belt. For segmenting the floor in 3D, we evaluate normal vectors and orientation of the camera obtained from depth and inertial data, respectively. Next, we apply RANSAC for computing efficiently the equation of the supporting plane (floor). The local grids are fused, obtaining a global map with data of free and occupied areas along the whole trajectory. For parallel processing of dense data, we leverage the capacity of the Jetson TX2, achieving high performance, low power consumption, and portability. Finally, we present experimental results obtained with ten (10) participants, in different conditions, with obstacles of different height, hanging obstacles, and dynamic obstacles. These results show high performance and acceptance by the participants, highlighting the easiness to follow instructions and the short period of training.

In this paper we present the methodology to build a vision-based wearable system that assists blind people in navigation tasks in unknown indoor environments. The proposed system detects walkable space, obstacles and objects of interest such as doors, chairs, staircases, computers, among others, and plans a path that allows the user to reach the objectives in a safe way (purposeful navigation). The system consists of six modules: for floor segmentation, for building an occupancy grid, for obstacle avoidance, for detecting objects of interest, for path planning and for haptic feedback to the user. Considering the big amount of data that a stereo camera delivers, the fact that the person is moving in a highly dynamic environment and the need of providing immediate feedback to the user, we defined two constraints: 1. Depth and color data must be processed at real time, in a general purpose graphics processing unit GPGPU. 2. Images must be processed in a wearable computer, it means, in a light and small processing device. Moreover, we defined trade-offs between sensing, computation and system usability that allow the system fulfill these requirements appropriately. The partial results in floor segmentation and in building the occupancy 2D grid encourage us to follow developing and improving the constituent modules.

Blind people present dificulties for reaching objects of interest in the daily life. In this sense, the integration of a path planning module for assisting blind people in purposeful navigation is noteworthy. In this work, we present an algorithm that leverages the high capability of an embedded computer with graphics processing unit (GPU) NVIDIA Jetson TX2 for computing optimal paths to objects of interest. The algorithm computes the optimal path to the objective, considering changes in the environment and changes in the position of the user. The algorithm is efficient for computing new paths when the environment changes by reusing parts of previous computations. In order to compare the performance, the algorithms were implemented and evaluated in MATLAB, C++ and CUDA, for different size of the grid and percentage of unknown obstacles. We found that the implementation on GPU has a speed up of 20 times W.R.T the implementation in C++ and more than 400 times W.R.T the implementation in MATLAB. These results boost us to integrate this module to our main system based on a stereo camera and a haptic belt and so provide to the user assistance in purposeful navigation at real time.

The hybrid in-band on-channel (IBOC) transmission system, which serves as a digital audio radio scheme, facilitates the simultaneous transmission of analog FM and digital audio. In IBOC systems, broadcasters transmit signals within allocated channel bands, posing a challenge in bandwidth allocation for digital audio transmission. To address this, cooperative game theory, supported by the bankruptcy game and Shapley’s value, is proposed as a strategy to optimize bandwidth allocation at each node or station. This approach considers service demand, the number of stations, and radio channel conditions in the FM band. The paper presents a scenario under saturated traffic conditions to evaluate the degree of optimization achievable using the Shapley value under clearly defined traffic and channel conditions. The results indicate that cooperative game theory, with the support of the Shapley value, offers an excellent alternative for optimizing bandwidth in digital broadcasting over IBOC in FM, with potential applicability in other digital radio broadcasting systems.

Dense Tracking, Mapping and Scene Labeling using a Depth Camera